294 Courses in Glasgow delivered On Demand

Explore the world of Artificial Intelligence with our comprehensive Foundations Course. From understanding the basics of AI and essential mathematical principles to delving into advanced topics like Deep Learning, Natural Language Processing, and Robotics – this course equips you with the knowledge and skills needed to navigate the dynamic landscape of AI. Whether you're a student, professional, or enthusiast, join us on a journey to build a solid foundation in AI and develop practical applications that shape the future. Enroll now and empower yourself to contribute to the exciting field of Artificial Intelligence.

Introduction to AI for Business

Who can apply for this MBA – Artificial Intelligence program? Anyone with an undergraduate degree with a minimum of 50% marks Minimum of one year of professional experience Professionals looking to grow their career with a Master degree in Management Professionals wishing to make a transition to mid-level and higher positions

Thinking about learning more about Artificial Intelligence? The BCS Foundation Certificate in Artificial Intelligence is the advanced version of our Essentials Course Artificial Intelligence and includes more detail and insights about algebraic equations, vector calculus and schematics used in artificial intelligence and machine learning for you to learn how this new technology works.

The BCS Essentials Certificate in Artificial Intelligence teaches the general principles of Artificial Intelligence, an introduction to Machine Learning and understand it's potential implications and capabilities. You will learn about human and artificial intelligence, the machine learning process, the different types of agents, the types of machine learning, the benefits, challenges and risks of a machine learning project, ethics in AI and the future of humans and machines in work. This is a great course for any person or organisation who needs to gain familiarity about Artificial Intelligence and Machine Learning before they commence a project; helping ensure the project approach is correct and avoid the common and costly pitfalls of technology projects.

About this training course Artificial lift systems are an important part of production operations for the entire lifecycle of an asset. Often, oil and gas wells require artificial lift for most of the life cycle. This 5-day training course offers a thorough treatment of artificial lift techniques including design and operation for production optimization. With the increasing need to optimize dynamic production in highly constrained cost environments, opportunities and issues related to real-time measurements and optimization techniques needs to be discussed and understood. Artificial lift selection and life cycle analysis are covered. These concepts are discussed and reinforced using case studies, quizzing tools, and exercises with software. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion. Understanding of these important production concepts is a must have to exploit the existing assets profitably. Unique Features: Hands-on usage of SNAP Software to solve gas-lift exercises Discussion on digital oil field Machine learning applications in gas-lift optimization Training Objectives After the completion of this training course, participants will be able to: Understand the basics and advanced concepts of each form of artificial lift systems including application envelope, relative strengths, and weaknesses Easily recognize the different components from downhole to the surface and their basic structural and operational features Design and analyze different components using appropriate software tools Understand challenges facing artificial lift applications and the mitigation of these challenges during selection, design, and operation Learn about the role of digital oilfield tools and techniques and their applications in artificial lift and production optimization Learn about use cases of Machine learning and artificial intelligence in the artificial lift Target Audience This training course is suitable and will greatly benefit the following specific groups: Production, reservoir, completion, drilling and facilities engineers, analysts, and operators Anyone interested in learning about selection, design, analysis and optimum operation of artificial lift and related production systems will benefit from this course. Course Level Intermediate Advanced Training Methods The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization. Course Duration: 5 days in total (35 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts. Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software. Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

About this Course This 5 full-day course presents the most modern statistical and mathematical forecasting frameworks used by practitioners to tackle the load forecasting problem across short time and long time scales. The course presents practical applications to solving forecasting challenges, supported by real life examples from large control areas. It presents the weather impacts on the load forecasts and the methodologies employed to quantify the weather effect and building a repository of weather normal data. A good load forecast methodology must improve its forecasting accuracy and support a consistent load forecasting process. The load forecasting widely used in the power industry has evolved significantly with the advancement and adoption of Artificial Intelligence techniques such as Machine Learning. With the increased penetration of inverter-based resources, the operation of electric grids grew in complexity, leading to load forecasts that are updated more frequently than once a day. Furthermore, several jurisdictions adopted a smaller granularity than the hourly load forecasts in the effort to reduce the forecasting uncertainties. On the generation side, fuel forecasting professionals must meet energy requirements while making allowance for the uncertainty on both the demand and the supply side. This training course will also feature a guest speaker, who is a Ph.D candidate to provide insights into the most modern aspects of Artificial Intelligence in the context of load forecasting. Training Objectives This course offers a comprehensive approach to all aspects of load forecasting: Gain a perspective of load forecasting from both operators in the generating plant and system operators. Understand and review the advanced load forecasting concepts and forecasting methodologies Learn the application of Artificial Neural Networks and Probabilistic Forecasting methods to manage forecasting uncertainties in short time frames Appreciate market segmentation and econometric framework for long term forecasts Find out the most recent practical application of load forecasting as examples from large power companies Get access to recent industry reports and developments Target Audience Energy load forecasting professionals from power plant and system operators Energy planners and energy outlook forecasters and plant operators Fuel procurement professionals Planners and schedulers of thermal generating units Course Level Intermediate Trainer Your expert course instructor is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Our Key expert delivered over 60 specialized seminars to executives and engineers from Canada, Europe, South and North America, Middle East, South East Asia and Japan. Few examples are: Modern Power System in Digital Utilities - The Energy Commission, Malaysia and utilities in the Middle East, GCCIA, June 2020 Assessment of OETC Control Centre, Oman, December 2019 Demand Side management, Load Forecasting in a Smart Grid, Oman, 2019 Renewable Resources in a Smart Grid (Malaysia, Thailand, Indonesia, GCCIA, Saudi Arabia) The Modern Power System: Impact of the Power Electronics on the Power System The Digital Utility, AI and Blockchain Smart Grid and Reliability of Distribution Systems, Cyme, Montreal, Canada Economic Dispatch in the context of an Energy Market (TNB, Sarawak Energy, Malaysia) Energy Markets, Risk Assessment and Financial Management, PES, IEEE: Chicago, San Francisco, New York, Portugal, South Africa, Japan. Provided training at CEO and CRO level. Enterprise Risk methodology, EDP, Portugal Energy Markets: Saudi Electricity Company, Tenaga National Berhad, Malaysia Reliability Centre Maintenance (South East Asia, Saudi Electricity Company, KSA) EUSN, ENERGY & UTILITIES SECTOR NETWORK, Government of Canada, 2016 Connected+, IOT, Toronto, Canada September 2016 and 2015 Smart Grid, Smart Home HomeConnect, Toronto, Canada November 2014 Wind Power: a Cautionary Tale, Ontario Centre for Public Policy, 2010 POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

Who is this course for? Sketchup Artificial Intelligence Training Course. Mastering SketchUp Artificial Intelligence (AI) is essential for designers, offering automation, efficiency, and innovative solutions. It saves time, enhances visualizations, fosters collaboration, and future-proofs skills, ensuring a competitive edge in the design industry. Click here for more info: Website How to Book? 1-on-1 training. Customize your schedule from Mon to Sat from 9 am to 7 pm Call to book  Duration: 16 hours. Method: In-person or Live Online Sketchup and (Artificial Intelligence) Stable Diffusion Rendering Course (16 hours) Module 1: Sketchup Fundamentals (2 hours) Sketchup software overview and interface navigation Introduction to basic drawing tools and fundamental geometry creation techniques Module 2: Texturing and Material Mastery (2 hours) Application of textures and customization of materials Exploration of texture mapping and comprehensive material libraries Module 3: Illumination and Shadows (2 hours) Comprehending lighting principles and strategic light placement Crafting realistic shadows and reflections Module 4: Advanced Modeling Techniques (3 hours) Creating intricate shapes and harnessing advanced modeling tools Efficiently managing groups, components, and modifiers Module 5: Stable Diffusion Rendering (2 hours) Initiating stable diffusion rendering Optimizing rendering settings for superior outcomes Module 6: Scene Composition and Camera Configuration (2 hours) Exploring composition principles and camera perspectives Scene management and creation of captivating walkthrough animations Module 7: Rendering Optimization Strategies (2 hours) Techniques for optimizing models to expedite rendering Application of render passes and post-processing methods Module 8: Real-World Projects and Portfolio Building (1 hour) Application of acquired skills in completing authentic projects Professional portfolio presentation techniques Optional: Stable Diffusion and Python Installation (Additional 10 hours) Module 1: Introduction to Stable Diffusion and Python Comprehensive understanding of Stable Diffusion and Python's significance Module 2: System Prerequisites Hardware and software requirements for successful installation Module 3: Python Installation Guide Step-by-step installation process for various operating systems Module 4: Configuring Python Environment Configuration of environment variables and package managers Module 5: Stable Diffusion Installation Downloading and installing the Stable Diffusion package Module 6: Setting Up the Development Environment Configuration of integrated development environments (IDEs) for Python and Stable Diffusion Module 7: Troubleshooting and Common Issues Identification and resolution of common installation errors Module 8: Best Practices and Recommendations Effective management of Python and Stable Diffusion installations Module 9: Practical Applications and Projects Hands-on exercises exemplifying the practical usage of Stable Diffusion and Python Module 10: Advanced Topics (Optional) Exploration of advanced features and techniques Stable Diffusion https://stablediffusionweb.com https://stable-diffusion-ui.github.io https://stability.ai/stable-diffusion Upon successful completion of the Sketchup and Stable Diffusion Rendering Course with a focus on AI image rendering, participants will achieve the following: 1. Mastery of AI Image Rendering: Attain expertise in employing AI-powered rendering techniques to produce realistic and top-quality visualizations. 2. Proficiency in Sketchup for 3D Modeling: Navigate the software adeptly, utilize drawing tools with proficiency, and craft intricate 3D models. 3. Enhanced Rendering Optimization: Implement AI-based rendering to enhance model visuals, resulting in faster rendering times and superior image quality. 4. Application of AI-driven Lighting and Shadows: Employ AI algorithms for precise lighting placement, shadows, and reflections, elevating the realism of renderings. 5. Development of a Professional Portfolio: Present AI-rendered projects within a polished professional portfolio, highlighting advanced image rendering capabilities. 1. Mastering Sketchup: Attain proficiency in Sketchup, a renowned and user-friendly 3D modeling software, equipping you with the skills needed to adeptly create and manipulate 3D models. 2. Advanced Rendering Expertise: Explore stable diffusion rendering, an avant-garde technique that simplifies the creation of realistic and high-quality renderings. Broaden your rendering capabilities, producing visually stunning representations of your designs. 3. Practical Industry Applications: Cultivate practical skills relevant to diverse industries, encompassing architecture, interior design, product development, and visualization. Elevate your professional portfolio with captivating renderings that showcase your design prowess. 4. Interactive Learning: Participate in hands-on exercises and projects that promote active learning and the practical application of concepts. Benefit from personalized feedback and expert guidance, ensuring your continuous progress throughout the course. 5. Career Advancement: Elevate your career prospects by adding valuable skills to your toolkit. Proficiency in crafting detailed 3D models and impressive renderings through stable diffusion techniques opens doors to diverse job opportunities within the design and visualization sector. 6. Flexibility and Convenience: Access course materials online and learn at your own pace. Enjoy the flexibility of tailoring the coursework to your schedule, allowing you to harmonize your learning journey with other commitments. Course Advantages: Tailored Learning: Enjoy personalized 1-on-1 sessions, accommodating your schedule from Monday to Saturday, 9 am to 7 pm. Mastery of Sketchup: Develop proficiency in the widely-used and user-friendly 3D modeling software, enabling efficient creation and manipulation of 3D models. Advanced Rendering Proficiency: Acquire expertise in stable diffusion rendering for producing realistic, high-quality renderings that enhance the visual appeal of your designs. Practical Applicability: Develop practical skills applicable across diverse domains, including architecture, interior design, product development, and visualization, enriching your professional portfolio. Interactive Practical Experience: Engage in hands-on exercises with personalized guidance from seasoned instructors, ensuring consistent progress in your skillset. Career Progression: Boost your career opportunities by gaining valuable skills in 3D modeling and generating impressive renderings through stable diffusion techniques. Comprehensive Support: Benefit from free portfolio reviews, mock interviews, and career advice, providing additional resources to enhance your professional journey.

About this Training Course There are various kinds of geophysical data available. They are separated into seismic and non-seismic (multi-physics) data. Non-seismic or multi-physics data (which includes gravity, magnetics, electrical, electromagnetics, spectral etc - apart from providing complimentary information to seismic) is the main source of information for very shallow subsurface applications such as engineering, mapping pollution, archaeology, geothermal energy, and related areas. This 5 full-day blended course will focus specifically on seismic data which is the main method used in the Oil & Gas industry. In this blended course, participants will be equipped to understand that seismic data represents the movement of the surface, resulting from waves generated by a source, dynamite or vibrator which are reflected by changes in the subsurface rocks. The basic principles of acquisition and processing will be explained and insights into advanced methods, allowing a much more accurate interpretation of seismic data than previously considered possible, will also be provided. This blended course contains an introduction to Machine Learning and its important role in all aspects of seismic acquisition, processing, and interpretation. There is no need to know in detail how the algorithms work internally but it is necessary to know how to use them correctly to achieve optimum results. Training Objectives By attending this course, participants will be able to acquire the following: Obtain an understanding of the strengths and limitations of geophysical methods, specifically seismic, and the costs and risks involved, and how to reduce these. Be able to communicate more effectively with staff in other disciplines. Understand the potential applications of seismic data and know how to formulate the requirements needed for prospect and field evaluation. Gain an awareness of modern seismic technology. Apply the learning in a series of practical, illustrative exercises. Know what types of questions to ask to assess the necessary quality of a seismic project in its role in a sequence of E&P activities Target Audience The blended course is intended for non-geophysicists who have intensive interaction with geophysicists. But it may be of interest to those who want to know about the recent progress made in geophysics, leading to amazing imaging results, which could not be imagined a decade ago. The blended course will bring to the attention of the geologists, petrophysicists and reservoir/petroleum engineers an awareness of how the data they will work with is acquired and processed by the geophysicist. It will introduce the concepts that are of importance in geophysics and thus relevant for non-geophysicists to know and be able to communicate with geophysicists as well as formulate their requests. Course Level Intermediate Trainer Your expert course leader has degree in Geology (University of Leiden), a Master's degree in Theoretical Geophysics (University of Utrecht) and a PhD in Utrecht on 'Full wave theory and the structure of the lower mantle'. This involved forward modelling of P- and S-waves diffracted around the core-mantle boundary and comparison of the frequency-dependent attenuation of the signal with those obtained from major earthquakes observed at long offsets in the 'shadow zone' of the core. These observations were then translated into rock properties of the D' transition zone. After his PhD, he joined Shell Research in The Netherlands to develop methods to predict lithology and pore-fluid based on seismic, petrophysical and geological data. He subsequently worked for Shell in London to interpret seismic data from the Central North Sea Graben. As part of the Quantitative Interpretation assignment, he was also actively involved in managing, processing and interpreting Offshore Seismic Profiling experiments. After his return to The Netherlands, he headed a team for the development of 3D interpretation methods using multi-attribute statistical and pattern recognition analysis on workstations. After a period of Quality Assurance of 'Contractor' software for seismic processing, he became responsible for Geophysics in the Shell Learning Centre. During that period, he was also a part-time professor in Applied Geophysics at the University of Utrecht. From 2001 to 2005, he worked on the development of Potential Field Methods (Gravity, Magnetics) for detecting oil and gas. Finally, he became a champion on the use of EM methods and became involved in designing acquisition, processing and interpretation methods for Marine Controlled Source EM (CSEM) methods. After his retirement from Shell, he founded his own company, specialising in courses on acquisition, processing and interpretation of geophysical data (seismic, gravity, magnetic and electromagnetic data), providing courses to International and National energy companies. In the last couple of years, he became keenly interested in the use of Machine Learning in Geophysics. Apart from incorporating 'Artificial Intelligence' in his courses, he also developed a dedicated Machine Learning course for geophysics. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

Artificial Intelligence Entrepreneurship